Online Workload Burst Detection for Efficient Predictive Autoscaling of Applications

Autoscaling methods are employed to ensure the scalability of cloud-hosted applications. The public-facing applications are prone to receive sudden workload bursts, and the existing autoscaling methods do not handle the bursty workloads gracefully. It is challenging to detect the burst online from t...

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Bibliographic Details
Main Authors: Fatima Tahir, Muhammad Abdullah, Faisal Bukhari, Khaled Mohamad Almustafa, Waheed Iqbal
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9069259/